Approximation and Estimation Bounds for Artificial Neural Networks
Machine Learning - Special issue on computational learning theory
Scheduling as a fuzzy multiple criteria optimization problem
Fuzzy Sets and Systems - Special issue on fuzzy multiple criteria decision making
Techniques for highly multiobjective optimisation: some nondominated points are better than others
Proceedings of the 9th annual conference on Genetic and evolutionary computation
An adaptive divide-and-conquer methodology for evolutionary multi-criterion optimisation
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
HEMO: a sustainable multi-objective evolutionary optimization framework
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Fast meta-models for local fusion of multiple predictive models
Applied Soft Computing
Many-Objective optimization: an engineering design perspective
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Preferences and their application in evolutionary multiobjectiveoptimization
IEEE Transactions on Evolutionary Computation
Evolutionary algorithms + domain knowledge = real-world evolutionary computation
IEEE Transactions on Evolutionary Computation
Efficient search for robust solutions by means of evolutionary algorithms and fitness approximation
IEEE Transactions on Evolutionary Computation
A family of dominance rules for multiattribute decision making under uncertainty
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Exploiting molecular dynamics for multi-objective optimization
Expert Systems with Applications: An International Journal
Linear programming approach for performance-driven data aggregation in networks of embedded sensors
Proceedings of the Conference on Design, Automation and Test in Europe
Grapheur: a software architecture for reactive and interactive optimization
LION'10 Proceedings of the 4th international conference on Learning and intelligent optimization
Diversity improvement by non-geometric binary crossover in evolutionary multiobjective optimization
IEEE Transactions on Evolutionary Computation
Decision engine for SIP based dynamic call routing
AIMS'11 Proceedings of the 5th international conference on Autonomous infrastructure, management, and security: managing the dynamics of networks and services
Lazy meta-learning: creating customized model ensembles on demand
WCCI'12 Proceedings of the 2012 World Congress conference on Advances in Computational Intelligence
Comparison of design concepts in multi-criteria decision-making using level diagrams
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Conjunction and disjunction operations for digital fuzzy hardware
Applied Soft Computing
Dynamic index tracking via multi-objective evolutionary algorithm
Applied Soft Computing
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We view Multicriteria Decision Making (MCDM) as the conjunction of three components: search, preference tradeoffs, and interactive visualization. The first MCDM component is the search process over the space of possible solutions to identify the non-dominated solutions that compose the Pareto set. The second component is the preference tradeoff process to select a single solution (or a small subset of solutions) from the Pareto set. The third component is the interactive visualization process to embed the decisionmaker in the solution refinement and selection loop. We focus on the intersection of these three components and we highlight some research challenges, representing gaps in the intersection. We introduce a requirement framework to compare most MCDM problems, their solutions, and analyze their performances. We focus on two research challenges and illustrate them with three case studies in electric power management, financial portfolio rebalancing, and air traffic planning.